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DBMS > Apache Impala vs. Datomic vs. Netezza vs. OpenQM

System Properties Comparison Apache Impala vs. Datomic vs. Netezza vs. OpenQM

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityData warehouse and analytics appliance part of IBM PureSystemsQpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSMultivalue DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websiteimpala.apache.orgwww.datomic.comwww.ibm.com/­products/­netezzawww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectIBMRocket Software, originally Martin Phillips
Initial release2013201220001993
Current release4.1.0, June 20221.0.6735, June 20233.4-12
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercialOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, Clojure
Server operating systemsLinuxAll OS with a Java VMLinux infoincluded in applianceAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeyesyesyesyes infowith some exceptions
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyesyes
TriggersnoBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and development
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUsers with fine-grained authorization conceptAccess rights can be defined down to the item level

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More resources
Apache ImpalaDatomicNetezza infoAlso called PureData System for Analytics by IBMOpenQM infoalso called QM
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Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Impala becomes Top-Level Project
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IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
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AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

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27 May 2020, AWS Blog

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